Impact of machine learning–based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease

2020 ◽  
Vol 30 (11) ◽  
pp. 5841-5851 ◽  
Author(s):  
Hong Yan Qiao ◽  
Chun Xiang Tang ◽  
U. Joseph Schoepf ◽  
Christian Tesche ◽  
Richard R. Bayer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Computed Tomography Angiography ◽  
Coronary Computed Tomography Angiography ◽  
Suspected Coronary Artery Disease ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Artery Disease

scholarly journals Noninvasive Assessment of Coronary Artery Disease: Fractional Flow Reserved Derived from Coronary Computed Tomography Angiography (FFRCT)

2016 ◽  
Vol 1 (2) ◽  
pp. 137-141
Author(s):  
Mihaela Rațiu ◽  
Nora Rat ◽  
Sebastian Condrea ◽  
Alexandra Stănescu ◽  
Diana Opincariu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Computed Tomography Angiography ◽  
Coronary Computed Tomography Angiography ◽  
Fractional Flow ◽  
Coronary Computed Tomography ◽  
Flow Reserve ◽  
Artery Disease ◽  
The Impact

AbstractInvasive coronary angiography (ICA) completed by fractional flow reserve (FFR) assessment represents the main procedure that is performed in the decision process for coronary revascularization. Coronary Computed Tomography Angiography (CCTA) is an effective method used in the noninvasive anatomic assessment of coronary artery disease (CAD). However, CCTA tends to overestimate and does not offer hemodynamic data about the coronary lesions. Recent progresses made in the research involving computational fluid dynamics and image modeling permit the evaluation of FFRCT noninvasively, using data obtained in a standard CCTA. Studies have shown an improved precision and discrimination of FFRCT compared to CCTA for the diagnosis of significant coronary artery stenosis. In this review, we aimed to summarize the role of CCTA in CAD evaluation, the impact of FFRCT, the scientific basis of this novel method and its potential clinical applications.

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